Previously, I wrote about some key takeaways from the DTx East conference in Boston and, specifically, on the state of digital therapeutics ‘today’.
Recurring themes that I heard, included: funding runways, new revenue models needed, Direct-To-Consumer (DTC), and Value-Based-Care (VBC). This week’s article will talk about increasing your product engagement and, as a result, generating value across multiple actors in the health ecosystem and making sure you don’t fall into some of the common traps we saw.
Anti-patterns! Common responses to what look like simple problems are an easy trap to fall into–and hard to break! These pitfalls are more prevalent when designing digital therapeutic solutions and they are more prevalent than we'd like to admit. Why's that? Well, in short, digital therapeutics is a rapidly evolving field, and companies are still navigating what works and, more importantly, what doesn’t. More often than not, people approach designing and building solutions without thinking through a more complex set of users–patients, providers, payers and more.
Combine this with the complexities of healthcare systems and the urgent need for adoption (funding and revenue are a big deal!), and it's a breeding ground for shortcuts and perceived quick fixes. Teams often lean into existing frameworks or get lured in by the promise of rapid development cycles, only to discover later that these paths undermine a solution's efficacy, scalability, or trustworthiness. While the stakes are high, the rules are still being written, making it too easy to stray into the land of anti-patterns.
Here are the most common anti-patterns we see that are critical blockers to a digital product’s success with users, clinicians, and payers:
- Lack of Clinical Validation: One common anti-pattern is rushing into development without robust clinical validation. Digital therapeutics should be evidence-based and evidence-led, backed by research to prove efficacy and value. Starting your product development before generating evidence of efficacy will lead to significant delays and poorly thought-through product design as you inevitably have to rework your solution. We often see this expressed via the fallacy of expert opinion; expertise, enhanced with evidence, is the way forward!
Because funding has felt the pinch lately, companies are looking to try and test new ways of revenue generation. One strategy that is being tested is accelerating getting products in the hands of patients by shifting to a direct-to-consumer (DTC) model; while this does offer a revenue path for companies that are failing to get traction in payer support or additional investment, avoid the temptation to move away from stringent evidence-based and evidence-led product design. DTC does not mean standards and best-practices can be skipped!
- Ignoring User-Centered Design: Neglecting user needs and preferences is a surefire route to failure. Digital therapeutics must be user-friendly and tailored to the needs of patients and healthcare providers. I recently co-hosted a webinar focused on “How to Build a Patient-Centric Solution in Healthcare”; one of our guests, Samson Magid, CEO of HealthSnap, made an insightful comment that we need to:
“build a solution that patients love, nurses don’t mind, and doctors don’t hate… it starts and ends with the patient experience….”
A lack of focus on patient needs means low engagement and product dropoff. Low patient engagement leads to less data and less value for a clinician in helping generate better outcomes. Low engagement and no evidence of improved outcomes mean payers will not support your product for reimbursement. Focus on these three types of users and the value you are bringing to each of them.Empathetic design helps empower patients and is a key element of inclusivity and trust. As my colleague, Rex Chekal, wrote, “just 18 percent of patients used a digital health app in 2021, a major drop from previous years. One reason for lagging adoption? A lack of empathy in design.”
The patient is not the only focus; for most digital therapeutics to work, they must meet the needs of both patients and practitioners and critically, they must not “be work” and should solve for users’ unmet needs.
A recent example that we worked through with a client was how to minimize the shame around symptoms; some patients are so embarrassed that they don’t even like to talk about the condition with their doctors. So, when building an app for this group, it’s mandatory that it makes these patients feel safe and validated. This allows the patient to be more open and the clinician to be made more aware.
- Inequity: In a push for speed-to-build and a culture of ‘domain expertise,’ non-diverse and inequitable research data is often used. Not taking the time to seek out broader, more diverse data that truly represents a full set of users and community ensures that your product, at best, will not get full adoption and, at worst, will be inaccurate and potentially dangerous.
A classic example is the pulse oximeter: researchers have known that these devices are less effective on darker skin tones for years. Their continued use and lack of adjustment in sensitivity and algorithms have continued to contribute to disparities in treatment. Inaccuracies that acutely impact care were introduced by not testing with a broader and more diverse patient base. Thankfully, researchers have focused on correcting this bias by focusing on more diverse patient groups.
- Overlooking Regulatory Compliance: Developing digital therapeutics often involves navigating complex regulatory frameworks. Going too far down the research or design process and not factoring in the relevant compliance requirements will lead to delays, fines, or even the inability to bring the product to market.
We recently helped a client think through their product strategy; we identified the relevant level of compliance needed (e.g. this was not going to be a medical device, and we didn’t qualify for the software pre-certification program), and we were confident that by designing a great patient experience we would be able to both demonstrate improved clinical significance via patient outcomes in both Randomized Clinical Trials (RCT) and through Real World Evidence (RWE).
By understanding the landscape of what was needed from a compliance standpoint, we focused our research and design to maximize success.
- Ignoring Clinician Integration: Overlooking the integration of digital therapeutics into the healthcare ecosystem is a significant anti-pattern. These solutions should complement the work of clinicians, not burden them. At a recent HLTH panel discussion in Las Vegas, Dr. Jesse Ehrenfeld (President of the AMA) reported a projected shortage of over 100,000 physicians in 10 years.
Failure to think through how to integrate with electronic health record systems (EHRs) and provide a seamless workflow experience for clinicians will contribute to increased clinician burnout and result in resistance to adoption and limited clinical buy-in.
So, how do we avoid these anti-patterns and more importantly, how do we ensure that your digital therapeutic product is embraced by patients, leads to significant adoption, is seen as valuable by clinicians, drives improved health outcomes and ultimately has a high degree of commercial viability? When we work with our clients, here are some key focus areas that we adhere to:
- Clear Goal Alignment: If gamification is used to drive engagement, ensure that the input and nudge elements align with the desired therapeutic goals. Define clear goals and objectives for users, whether managing chronic conditions, improving mental health, or encouraging healthier behaviours. Gamification should support these objectives and not just be designed to generate dopamine hits
Fitbit was a great early example of how to approach gamifying their product to encourage increased adoption and usage; at its heart, the step-tracking app showed you your progress; but for those that wanted increased accountability or even competitiveness, the product evolved to bring in community. Users could set challenges or just share progress depending on what they wanted to achieve.
There was a specific purpose and utility to the gamification model used that tied directly to a user need.
- Progress Tracking: Ensure you implement a system for users to track their progress easily and contextually. This could be through visual dashboards, achievement badges, or progress bars. Showing users how far they've come can be highly motivating, but making users aware of the context of their progression helps build a connection.
If the user is still in the ‘data gathering’ phase of their app journey, make them aware of that, or else they may be expecting insights and feedback that isn’t appropriate yet.
- Social Integration: Incorporate social features to foster a sense of community and contribution. We know from research insights that people are willing to share their health journeys–whether as patients or caregivers. Look at social media platforms such as Facebook or Reddit, and you will find innumerable user groups and communities sharing stories and tips.
We frequently hear from users that knowing they are providing support and data back to their patient community and the research/clinical teams motivates them even more than the benefit they may see for themselves.
- Personalization: As much as possible, tailor to individual preferences and needs. Use data-driven insights to understand how and when patients use their digital therapeutic. Focus early on what strong engagement looks like and ensure you can measure that accurately. Then, adapt challenges, goals, or rewards based on a user's engagement progress and health status. As seen from the list above, personalization, social engagement (not just social media), contextual progress tracking, and driving to aligned goals increase user relevance and engagement.
Care at scale has enforced a model of the system defining the individual–patients being told what to do within the rigid constraints of “show up here, at this time…and don’t bother telling us anything we don’t ask you”. Digital Therapeutic solutions that are personalized, and meet the user where they are in their life, will allow the individual to define the systems they use, and these solutions will ultimately be the winners.
Personalized care, tailored and refined over time, based on the specific data from that patient versus just based on a general population or cohort approach will also lead to increased care outcomes and reduced burden on clinicians and health systems.
- Storytelling: Finally, weave storytelling into the user's journey. Create compelling narratives that resonate with users, making them feel like the hero of their own health story. This emotional connection can keep users engaged over the long term. Similarly, ensure you know what information and when a patient or care provider needs it. Finally, being able to tell and show the right story for patients and clinicians (within their workflow) helps providers buy into the product and the data you are providing them.
From experience, we know that getting KOL and clinician buy-in because they trust the data and the mechanism used to generate it from patients in real-world scenarios leads to improved care outcomes.
Attending DTx East in Boston was a good reminder of where we are today and what we should keep focusing on to keep moving forward; however, one area that we haven’t touched on yet is equity and accessibility. If you are not designing your solution to be equitable and accessible, you are actively choosing to exclude millions of users. I’ll be writing about this next week!
